Pretty pie charts using k-means clustering of images in R

pretty-pie.R

# adapted from http://is-r.tumblr.com/post/36660147376/dominant-color-palettes-with-k-means

library(ggplot2)
library(reshape2)
library(EBImage)

imageLoader <- function(lib) { 
  rd <- readImage(lib)
  longImage <- melt(rd)
  rgbImage <- reshape(longImage, timevar="Var3", idvar=c("Var1", "Var2"), direction="wide")
  rgbImage$Var1 <- -rgbImage$Var1
  return(rgbImage)
}

# find image URL
rgbImage <- imageLoader("http://www.tate.org.uk/art/images/work/T/T03/T03254_10.jpg")

kColors <- 5
kMeans  <- kmeans(rgbImage[, 3:5], centers=kColors)
zp1 <- qplot(factor(kMeans$cluster), geom="bar", fill=factor(kMeans$cluster))
zp1 <- zp1 + scale_fill_manual(values=rgb(kMeans$centers))

approximateColor <- kMeans$centers[kMeans$cluster, ]

ggplot(as.data.frame(kMeans$cluster), aes(x=factor(1), fill=factor(kMeans$cluster))) + 
  geom_bar(width=1) + 
  scale_fill_manual(values=rgb(kMeans$centers)) + 
  coord_polar(theta="y") + 
  theme(panel.background=element_blank(),
        axis.title=element_blank(), 
        axis.ticks=element_blank(), 
        panel.grid=element_blank(), 
        axis.text.y=element_blank(),
        legend.position="none", 
        axis.text.x=element_blank()) + 
  ylab("") + 
  xlab("")
  
ggsave(file="prettypie.png")